Text Classification
Transformers
PyTorch
Safetensors
Turkish
English
convbert
Trained with AutoTrain
Instructions to use tolgadev/TurkishAirlines-SentimentAnalysisModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tolgadev/TurkishAirlines-SentimentAnalysisModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tolgadev/TurkishAirlines-SentimentAnalysisModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tolgadev/TurkishAirlines-SentimentAnalysisModel") model = AutoModelForSequenceClassification.from_pretrained("tolgadev/TurkishAirlines-SentimentAnalysisModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Tolga commited on
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Parent(s): 4d40187
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README.md
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You can use cURL to access this model:
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```
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love to fly with Turkish Airlines"}' https://api-inference.huggingface.co/models/tkurtulus/
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```
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Or Python API:
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```
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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model = AutoModelForSequenceClassification.from_pretrained("tkurtulus/
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tokenizer = AutoTokenizer.from_pretrained("tkurtulus/
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inputs = tokenizer("I love to fly with Turkish Airlines", return_tensors="pt")
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You can use cURL to access this model:
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```
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$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love to fly with Turkish Airlines"}' https://api-inference.huggingface.co/models/tkurtulus/TurkishAirlines-SentimentAnalysisModel
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```
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Or Python API:
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```
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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model = AutoModelForSequenceClassification.from_pretrained("tkurtulus/TurkishAirlines-SentimentAnalysisModel")
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tokenizer = AutoTokenizer.from_pretrained("tkurtulus/TurkishAirlines-SentimentAnalysisModel")
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inputs = tokenizer("I love to fly with Turkish Airlines", return_tensors="pt")
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